Tried to fix changes from skosch
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@ -201,59 +201,32 @@ module T =
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each discrete data point, and then adds them all together. */
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let combineAlgebraicallyWithDiscrete =
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(
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~downsample=false,
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op: ExpressionTypes.algebraicOperation,
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t1: t,
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t2: DistTypes.discreteShape,
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) => {
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let t1s = t1 |> getShape;
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let t2s = t2.xyShape; // would like to use Discrete.getShape here, but current file structure doesn't allow for that
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let t1n = t1s |> XYShape.T.length;
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let t2n = t2s |> XYShape.T.length;
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let fn = Operation.Algebraic.toFn(op);
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let outXYShapes: array(array((float, float))) =
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Belt.Array.makeUninitializedUnsafe(t2n);
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for (j in 0 to t2n - 1) {
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// for each one of the discrete points
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// create a new distribution, as long as the original continuous one
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let dxyShape: array((float, float)) =
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Belt.Array.makeUninitializedUnsafe(t1n);
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for (i in 0 to t1n - 1) {
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let _ =
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Belt.Array.set(
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dxyShape,
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i,
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(fn(t1s.xs[i], t2s.xs[j]), t1s.ys[i] *. t2s.ys[j]),
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);
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();
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};
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let _ = Belt.Array.set(outXYShapes, j, dxyShape);
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();
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let s1 = t1 |> getShape;
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let s2 = t2.xyShape;
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let t1n = s1 |> XYShape.T.length;
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let t2n = s2 |> XYShape.T.length;
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if (t1n == 0 || t2n == 0) {
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empty;
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} else {
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let combinedShape =
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AlgebraicShapeCombination.combineShapesContinuousDiscrete(op, s1, s2);
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let combinedIntegralSum =
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Common.combineIntegralSums(
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(a, b) => Some(a *. b),
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t1.knownIntegralSum,
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t2.knownIntegralSum,
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);
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// return a new Continuous distribution
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make(`Linear, combinedShape, combinedIntegralSum);
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};
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let combinedIntegralSum =
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Common.combineIntegralSums(
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(a, b) => Some(a *. b),
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t1.knownIntegralSum,
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t2.knownIntegralSum,
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);
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outXYShapes
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|> E.A.fmap(s => {
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let xyShape = XYShape.T.fromZippedArray(s);
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make(`Linear, xyShape, None);
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})
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|> reduce((+.))
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|> updateKnownIntegralSum(combinedIntegralSum);
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};
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let combineAlgebraically =
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(~downsample=false, op: ExpressionTypes.algebraicOperation, t1: t, t2: t) => {
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(op: ExpressionTypes.algebraicOperation, t1: t, t2: t) => {
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let s1 = t1 |> getShape;
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let s2 = t2 |> getShape;
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let t1n = s1 |> XYShape.T.length;
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@ -257,7 +257,7 @@ module T =
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});
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let combineAlgebraically =
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(~downsample=false, op: ExpressionTypes.algebraicOperation, t1: t, t2: t)
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(op: ExpressionTypes.algebraicOperation, t1: t, t2: t)
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: t => {
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// Discrete convolution can cause a huge increase in the number of samples,
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// so we'll first downsample.
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@ -265,33 +265,31 @@ let combineAlgebraically =
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// An alternative (to be explored in the future) may be to first perform the full convolution and then to downsample the result;
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// to use non-uniform fast Fourier transforms (for addition only), add web workers or gpu.js, etc. ...
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let downsampleIfTooLarge = (t: t) => {
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let sqtl = sqrt(float_of_int(totalLength(t)));
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sqtl > 10. && downsample ? T.downsample(int_of_float(sqtl), t) : t;
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};
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// we have to figure out where to downsample, and how to effectively
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//let downsampleIfTooLarge = (t: t) => {
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// let sqtl = sqrt(float_of_int(totalLength(t)));
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// sqtl > 10 ? T.downsample(int_of_float(sqtl), t) : t;
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//};
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let t1d = downsampleIfTooLarge(t1);
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let t2d = downsampleIfTooLarge(t2);
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let t1d = t1;
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let t2d = t2;
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// continuous (*) continuous => continuous, but also
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// discrete (*) continuous => continuous (and vice versa). We have to take care of all combos and then combine them:
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let ccConvResult =
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Continuous.combineAlgebraically(
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~downsample=false,
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op,
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t1d.continuous,
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t2d.continuous,
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);
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let dcConvResult =
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Continuous.combineAlgebraicallyWithDiscrete(
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~downsample=false,
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op,
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t2d.continuous,
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t1d.discrete,
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);
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let cdConvResult =
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Continuous.combineAlgebraicallyWithDiscrete(
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~downsample=false,
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op,
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t1d.continuous,
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t2d.discrete,
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@ -27,14 +27,13 @@ let combineAlgebraically =
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switch (t1, t2) {
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| (Continuous(m1), Continuous(m2)) =>
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DistTypes.Continuous(
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Continuous.combineAlgebraically(~downsample=true, op, m1, m2),
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Continuous.combineAlgebraically(op, m1, m2),
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)
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| (Discrete(m1), Discrete(m2)) =>
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DistTypes.Discrete(Discrete.combineAlgebraically(op, m1, m2))
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| (m1, m2) =>
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DistTypes.Mixed(
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Mixed.combineAlgebraically(
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~downsample=true,
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op,
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toMixed(m1),
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toMixed(m2),
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